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There is a reason the OECD proposed two pillars for its gateway to a better tax future. A gateway requires both pillars, and neither can stand without the other. Pillar 2 is a fait accompli, but it needs countries to implement Pillar 1 as well because in the absence of a clear sourcing rule there is no limit to countries implementing the Qualified Domestic Minimum Top-Up Tax (QDMTT), which would turn off the other parts of Pillar 2 and potentially result in double taxation. Pillar 1 is not going forward in the absence of a Multilateral Tax Convention (MLC), but it can be implemented unilaterally, although that would require overriding existing tax treaties.

There is a reason the OECD proposed two pillars for its gateway to a better tax future. A gateway requires both pillars, and neither can stand without the other. Pillar 2 is a fait accompli, but it needs countries to implement Pillar 1 as well because in the absence of a clear sourcing rule there is no limit to countries implementing the Qualified Domestic Minimum Top-Up Tax (QDMTT), which would turn off the other parts of Pillar 2 and potentially result in double taxation. Pillar 1 is not going forward in the absence of a Multilateral Tax Convention (MLC), but it can be implemented unilaterally, although that would require overriding existing tax treaties.

ABSTRACTSolid waste has surfaced as an eminent and critical concern of environmental and social significance on a global scale, and Ethiopia, a developing country with limited income, has also encountered unfavorable outcomes due to substandard waste management practices. When pinpointing a fitting landfill location in the town of Bule Hora, various ecological, economic, and societal aspects must be considered; these may result in discord and exacerbate a multifaceted and lengthy process. Hence, this research aims to identify prospective landfill sites within the town and utilize geospatial methods, such as Multi-Criteria Evaluation and Analytic Hierarchy Process, to accomplish its objectives. The utilization of geospatial technology and multi-criteria evaluation provides an efficient manner to simultaneously address all bottlenecks involved in the selection of an appropriate landfill location. Geospatial technology evaluates and manages environmental constraints, whereas multi-criteria assessment categorizes choices based on their desirability. Furthermore, by employing a restriction map adhering to established standards, seven landfill sites have successfully been identified within the town. The Land Suitability Index assesses site suitability based on ecological factors, while the Total Hauling Distance evaluates sites within an economic framework. AHP determines weightings through 25.4 pairwise comparisons, resulting in a consistency ratio of 1.95%. The cartographic analysis is conducted using ESRI ArcGIS version 10.8 software. The findings of this study reveal that 98.69% of the area under study is subject to restrictions. The study recommends the implementation of geospatial methods for identifying suitable landfill sites, which would aid in the decision-making process and prevent hasty decisions from triggering environmental degradation. Proper waste disposal would augment the quality of life for residents by diminishing health hazards. The study endeavors to serve as a reference for other developing countries in selecting appropriate landfill sites.Implications: The town of Bule Hora also faces the problem of waste disposal; there is no scientifically selected suitable landfill. Residents of the town of Bule Hora practice waste disposal in open fields, near settlements, water bodies, roads, agricultural land, and other places. The main sources of solid waste in the town are homes, shops, hotels, restaurants, open markets, hospitals, educational institutions, private clinics, etc. Water pollution can potentially lead to the spread of waterborne diseases. According to reports from the Bule Horas Health Department, many people are affected by water-related diseases every year. These open landfill systems with no regard for settlement, topography, geology, surface, or groundwater conditions are the consequences of these unsuitable habitats and health problems. To reduce these problems, this study plays an important role in determining the suitability of landfills for the town and proposing alternative measures that can minimize negative environmental impacts from waste. This study aims to apply geospatial-based technology to a multi-criteria assessment technique to select perfectly suitable landfill sites that are environmentally friendly, economically cost-effective, and socially responsible; examine the town’s current waste management system; calculate the selected parameter weights for feature ranking; and delineate solid waste landfills.

Background Glomus jugulare is a rare, slow-growing tumor that arise within the jugular foramen of the temporal bone. In the past, surgery was the primary modality of treatment for glomus Jugulare, but it leads to many complications and increased mortality. Radiotherapy was indicated in adjuvant setting in post-operative residual disease. But, with the advent of highly conformal radiation planning, stereotactic radiosurgery (SRS), is now one of the main modalities of radiation treatment in glomus jugulare.Objective To describe the procedural steps for radiation planning of SRS of glomus jugulare.Methods The step-by-step procedure for stereotactic planning of glomus jugulare has been described using a clinical scenario of glomus jugulare.Results The stereotactic radiation planning of glomus jugulare starts with the basic history and relevant clinical evaluation, that is, visual testing. Computed tomography (CT) scan and magnetic resonance imaging (MRI) of the brain is the imaging modality of choice. The radiation planning of glomus jugulare starts with CT simulation. MRI of brain should be done in the prescribed format to achieve uniformity in radiation planning. After CT and MRI image fusion, contouring of target, organs at risk (OAR) and radiation planning should be done. The plan evaluation includes target and OAR coverage index, conformity, homogeneity and gradient index, and beam arrangement. After radiation plan evaluation, treatment is delivered after quality assurance and dry run.Conclusion The paper highlights the sequential process of radiation planning for SRS in glomus jugulare—starting from simulation, planning, evaluation of plan, and treatment.

Brain metastasis is seen in 10% to 20% of all adult cancer patients. One of the main modalities of treatment is stereotactic radiosurgery (SRS). Here, we describe the step by step procedure for stereotactic planning of brain metastasis by using a clinical scenario. The management of brain metastasis starts with the clinical evaluation of the patient followed by imaging and SRS treatment in the present case. The paper highlights the sequential process of radiation planning for SRS—starting from simulation, planning, evaluation of plan, and treatment.

Primary testicular lymphoma (PTL) is a rare variant of non-Hodgkin’s lymphoma that is predominant in old age group. Painless testicular swelling is the most common presentation. The standard of care is surgery in the form of radical orchiectomy followed by adjuvant chemotherapy and central nervous system prophylaxis. Because of blood-testis barrier, contralateral testis acts as a sanctuary site for chemotherapy to act and hence scrototesticular radiation is advocated in order to reduce the chance of testicular relapse. Due to lack of any consensus simulation procedure, we propose here a step-by-step procedure for simulation of a case of PTL using a case scenario.

With the rise of Big Data, there has been a significant effort in increasing compute power through GPUs, TPUs, and heterogeneous architectures. As a result, many applications are memory bound, i.e., they are bottlenecked by the movement of data from main memory to compute units. One way to address this issue is through data prefetching, which relies on accurate prediction of memory accesses. While recent deep learning models have performed well on sequence prediction problems, they are far too heavy in terms of model size and inference latency to be practical for data prefetching. Here, we propose clustering-driven compact LSTM models that can predict the next memory access with high accuracy. We introduce a novel clustering approach called Delegated model that can reliably cluster the applications. For each cluster, we train a compact meta-LSTM model that can quickly adapt to any application in the cluster. Prior LSTM-based work on access prediction has used orders of magnitude more parameters and developed one model for each application (trace). While one (specialized) model per application can result in more accuracy, it is not a scalable approach. In contrast, our models can predict for a class of applications by trading off specialization at the cost of few retraining steps at runtime, for a more generalizable compact meta-model. Our experiments on 13 benchmark applications demonstrate that clustering-driven ensemble compact meta-models can obtain accuracy close to specialized models using few batches of retraining for majority of the applications.

Background: Nowadays, there is an immense increase in the demand for high power computation of real-time workloads and the trend towards multi-core and multiprocessor CPUs. The realtime system needs to be implemented upon multiprocessor platforms. Introduction: The nature of processors in an embedded real-time system is changing day by day. The two most significant challenges in a multiprocessor environment are scheduling and synchronization. The popularity of real-time multi-core systems has exploded in recent years, driving the rapid development of a variety of methods for multiprocessor scheduling of essential tasks; on the other hand; these systems have constraints when it comes to maintaining synchronization in order to access shared resources. Methods: This research work presents a systematic review of different existing scheduling algorithms and synchronization protocols for shared resources in a real-time multiprocessor environment. The manuscript also presents a study based on various metrics of resource scheduling and comparison among different resource scheduling techniques. Conclusion: The survey classifies open issues, key challenges, and likely useful research directions. Finally, we accept that there is still a lot of capacity in developing better resource management and further maintaining the overall quality. The paper considers such a future path of research in this field.

Within the advanced computation time, real-time application pulled in much more attention. Implementing a better high-quality real-time system requires to improve the responsiveness of the tasks set. This research work aims to achieve the best quality of service (QoS) in terms of improving the responsiveness of aperiodic tasks and also improved acceptability domain, by accepting to execute multiple aperiodic functions while maintaining the feasibility of periodic tasks in a real-time system.The functional analysis with simulation shows that the proposed algorithm is highly effective in terms of task sets deemed schedulable and also by allowing aperiodic tasks that were rejected by existing approaches. The simulation results indicate that it reduces overall average response time of aperiodic tasks approximately 13% at lowest periodic load (35%), 7% at 60% periodic load, and 4% at 80% periodic load, and in all observed circumstances, the proposed novel algorithm received 7%-10% improvement over the existing one.

Background: NSAIDs are the most widely prescribed medications worldwide for their anti-inflammatory, antipyretic, and analgesic effects. However, their chronic use can lead to several adverse drug events including GI toxicity. The selective COX-2 inhibitors developed as gastrosparing NSAIDs also suffer from serious adverse effects which limit their efficacy. Objective: Local generation of reactive oxygen species is implicated in NSAID-mediated gastric ulceration and their combination with H2 antagonists like famotidine reduces the risk of ulcers. The objective of this work was to design and synthesize novel methanesulphonamido isoxazole derivatives by hybridizing the structural features of NSAIDs with those of antiulcer drugs (ranitidine, famotidine, etc.) to utilize a dual combination of anti-inflammatory activity and reducing (antioxidant) potential. Methods: The designing process utilized three dimensional similarity studies and utilized an isoxazole core having a potential for anti-inflammatory as well as radical scavenging antioxidant activity. The compounds were assayed for their anti-inflammatory activity in established in vivo models. The in vitro antioxidant activity was assessed in potassium ferricyanide reducing power (PFRAP) assay employing ascorbic acid as the standard drug. Results: Compounds 5, 6, 9 and 10 showed antiinflammatory activity comparable to the standard drugs and were also found to be non-ulcerogenic at the test doses. Compounds 6-10 exhibited good antioxidant effect in the concentration range of 1.0- 50.0 μmol/ml. The test compounds were also found to comply with the Lipinski rule suggesting good oral absorption. Conclusion: A new series of isoxazole based compounds is being reported with good antiinflammatory activity coupled with antioxidant potential as gastro-sparing anti-inflammatory agents.

Energy consumption of embedded applications has rapidly increased with the advancement of technology and computing. There is a little improvement in energy consumption as compared to computing and storage capacity. Although computing performance has been continuously increasing, power/energy consumption is more critical in the design of real-time embedded systems. Real-time embedded applications need a power management technique to judicially balance the energy consumption and computing performance. It should be done in such a way that the system performance improves along with an increase in the lifespan of the system. The proposed methodology presented in this paper deals with the minimization of energy for time-critical embedded applications. Simulation studies, along with theoretical analysis, have been carried out to show the effectiveness of the proposed three-phase reliable energy-aware scheduling method. It is observed that the proposed approach provides better tolerance (approximately four times) and consumes less energy (35% to 45%) for a wide range of applications.

Background:Stereotactic body radiotherapy (SBRT) is an important treatment modality in liver metastasis in which surgery is not feasible or when the patient denies surgery. With the recent advances in treatment planning systems and real-time image-guided treatment delivery, we can now deliver high doses of radiation in a small number of fractions to the target with high precision and minimal dose to the organs at risk (OARs).Objective:To describe the procedural steps for radiation planning of SBRT of Liver Metastasis.Methods:The step-by-step procedure for stereotactic planning of liver metastasis has been described using a clinical scenario of liver metastasis.Results:The stereotactic radiation planning of liver metastasis starts with the basic history and relevant clinical evaluation followed by tissue confirmation of the diagnosis of liver metastasis. The SBRT planning for liver metastasis starts with the positioning of the patient using a body immobilization device. This is followed by the use of any of the motion management techniques during the computed tomography (CT) simulation. Magnetic resonance imaging (MRI) of the abdomen should be done in the prescribed format to achieve uniformity in radiation planning. After CT and MRI image fusion, contouring of the target, OARs, and radiation planning should be done. The plan evaluation includes target and OAR coverage index, conformity, homogeneity gradient index, and beam arrangement. After radiation plan evaluation, quality assurance and dry run are done. Then treatment is delivered using the same motion management technique that was used during the CT simulation.Conclusion:The article highlights the sequential process of radiation planning for SBRT in liver metastasis―starting from simulation, planning, evaluation of plan, and treatment

In a piping system, pipe bends are more flexible than straight pipes because of their curved geometry, supplemented by higher stress and strain concentration, leading to one of the crucial components in piping industries. Therefore, safe design of pipe bends is essential for smooth running of the piping system, and plastic collapse moment is one of its criteria. This paper utilizes three-dimensional finite element analyses to model empirical solutions for the plastic collapse moment for different angled pipe bends subjected to combined pressure and in-plane closing, in-plane opening, and out-of-plane bending moments. Plastic collapse moments for 30∘ to 180∘ pipe bends are determined for elastic perfectly plastic and strain hardening materials, employing large geometry change option and internal pressure effect. It is observed from results that pressure effect is more prominent in thinner pipe bends of larger bend angle under all bending cases. For in-plane opening and out-of-plane bending moments, collapse moment increases and then decreases with increase in pressure intensity for all sizes of pipe bend. However, for in-plane opening bending moment, collapse moments keep on decreasing for thicker (r/t= 11.33) pipe bends. Finally, the study presents new improved plastic collapse moment solutions for different angled pipe bends under bending moment and internal pressure, derived from the finite element results of elastic perfectly plastic and strain hardening material models.

Objective:This study examined the impact of a peer-based mindfulness and yoga intervention to reduce interpersonal violence in a network of young adults experiencing homelessness (YAEH). Method:A network of YAEH (n=58) accessing homelessness drop-in services in Los Angeles, CA, completed a baseline and follow-up self-administered survey. After applying a violence minimization machine-learning algorithm to baseline data, 12 YAEH were identified and invited to participate in the Mindfulness and Yoga Peer Ambassador Training for Health (MYPATH). The training consisted of a 3-hour intensive followed by seven weekly 1-hour sessions. The training introduced mindfulness and yoga as tools and practices to increase emotion regulation and reduce impulsivity in the context of interpersonal and community violence. Follow-up data were collected 2 months after baseline. Results:Results revealed increased trait mindfulness (i.e., a tendency or trait rather than a particular practice or in-the-moment experience), increased mindfulness and yoga practice frequency, and reduced violence-engagement behaviors in the network of YAEH. Conclusions:The current study provides preliminary support for the effectiveness of the intervention in decreasing network-level violence and demonstrates the feasibility of implementing a peer-based intervention to promote mindfulness and yoga practice in a network of YAEH.

Background: NSAIDs are used as first-line drugs for the treatment of various inflammatory disorders. Chronic use of NSAIDs is known to be associated with gastrointestinal and renal toxicity. Local generation of reactive oxygen species finally resulting in cellular apoptosis is one of the accepted mechanisms for NSAID-induced toxicity. Objective: The objective of the present study was to design and synthesize a series of 2-methane sulfonamido substituted arylthiazole derivatives by including structural features of combined antiulcer and anti-inflammatory activity utilizing as the structural core, thiazole nucleus with potential for antioxidant effect. Methods: Compounds were designed based on three dimensional and field similarity studies. The synthesized compounds were evaluated for their anti-inflammatory activity in carrageenan-induced rat paw edema model. Rofecoxib and indomethacin were taken as standard drugs for comparison. The in vitro antioxidant activity was assessed in potassium ferricyanide reducing power (PFRAP) assay employing ascorbic acid as the standard drug. Results: The compounds 6 and 7 showed good anti-inflammatory activity comparable to the standard group and were also non ulcerogenic at the test doses. Compounds 1-7 displayed varying degrees of reducing power in the PFRAP) assay and the methanesulphonamido derivatives 4-7 showed the highest antioxidant activity (EC50 values 3.7-5.1 μmol/ml vs ascorbic acid 7.4 μmol/ml). Theoretical ADME profiling of the compounds based on selected physicochemical properties showed excellent compliance with Lipinski’s rule. Conclusion: A series of compounds have been designed and synthesized having dual antioxidant and anti-inflammatory activity with activities comparable to standard drugs.

Multiprocessor real-time systems receive a great deal of attention. For better utilization of multiprocessors in a real-time context, an optimal approach for scheduling, allocation, and synchronization is required. In this research, a novel heuristic synchronization-aware scheduling has been proposed to reduce the blocking delays in a critical section and also bound to minimize multiple priority inversion. The key idea of this technique is to assign the task set in the same processor that accesses a common shared resource and also access them for the longest period of time; thereby, the global sharing of resource transforms into local sharing. From simulation results, it was concluded that the duration of blocking overheads should be minimized up to 25% to 30% and context switching between processors also reduced up to 10% to 15%. On the basis of result analysis, schedulability, minimization of context switching, and reduced blocking time indicate that the proposed method outperforms the existing methods and does not affect the task completion time.

The COVID-19 Scenario Modeling Hub convened nine modeling teams to project the impact of expanding SARS-CoV-2 vaccination to children aged 5–11 years on COVID-19 burden and resilience against variant strains.

Often in marketing, political campaigns and social media, two competing products or opinions propagate over a social network. Studying social influence in such competing cascade scenarios enables building effective strategies for maximizing the propagation of one process by targeting the most “influential” nodes in the network. The majority of prior work, however, focuses on unsigned networks where individuals adopt the opinion of their neighbors with certain probability. In real life, relationships between individuals can be positive (e.g., friend of relationship) or negative (e.g., connection between “foes”). According to social theory, people tend to have similar opinions to their friends but opposite of their foes. We study the problem of competing cascades on signed networks, which has been relatively unexplored. Particularly, we study the progressive propagation of two competing cascades in a signed network under the Independent Cascade Model and Generalized Linear Threshold Model and provide an approximate analytical solution to compute the probability of infection of a node at any given time. We validate the quality of our approximation on several synthetic graphs. We leverage our analytical solution to the problem of competing cascades in signed networks to develop a heuristic for the influence maximization problem. We allow the seed-set to be initialized with populations of both cascades with the end goal of maximizing the spread of one cascade. We validate our approach on several large-scale real-world and synthetic networks. Our experiments demonstrate that our influence maximization heuristic significantly outperforms state-of-the-art methods, particularly when the network is dominated by distrust relationships.

The study of information dissemination on a social network has gained significant importance with the rise of social media. Since the true dynamics are hidden, various diffusion models have been exposed to explain the cascading behavior. Such models require extensive simulation for estimating the dissemination over time. In an earlier work, we proposed a unified model which provides an approximate analytical solution to the problem of predicting probability of infection of every node in the network over time. Our model generalizes a large class of diffusion process. We demonstrate through extensive empirical evaluation that the error of approximation is small. We build upon our unified model to develop an efficient method for influence maximization. Unlike most approaches, we assume that diffusion spreads not only via the edges of the underlying network, but also through temporal functions of external out-of-network processes. We empirically evaluate our approach and compare it against state-of-the-art approaches on real-world large-scale networks. The evaluation demonstrates that our method has significant performance gains over widely used seed-set selection algorithms.

Osteolysis, caused by active resorption of bone matrix by osteoclasts, can be primary or can develop secondary to a variety of disease processes. An elevated level of inflammatory cytokines in the local milieu and increased blood flow secondary to infection or autonomic neuropathy stimulate the osteoclasts and cause bone loss in the diabetic foot. Charcot's neuroarthropathy and osteomyelitis are well-known foot complications of diabetes, and secondary osteolysis has largely been underappreciated and, hence, underreported. Plain radiographs, an initial component in the evaluation of the diabetic foot, may not successfully differentiate secondary osteolysis from osteomyelitis. We describe a patient with phalangeal osteolysis secondary to soft-tissue infection in whom a correct and timely diagnosis helped avoid unnecessary surgical interventions.

Popular social networking sites have revolutionized the way people interact on the Web, enabling rapid information dissemination and search. In an enterprise, understanding how information flows within and between organizational levels and business units is of great importance. Despite numerous studies in information diffusion in online social networks, little is known about factors that affect the dynamics of technological adoption at the workplace. Here, we address this problem, by examining the impact of organizational hierarchy in adopting new technologies in the enterprise. Our study suggests that middle-level managers are more successful in influencing employees into adopting a new microblogging service. Further, we reveal two distinct patterns of peer pressure, based on which employees are not only more likely to adopt the service, but the rate at which they do so quickens as the popularity of the new technology increases. We integrate our findings into two intuitive, realistic agent-based computational models that capture the dynamics of adoption at both microscopic and macroscopic levels. We evaluate our models in a real-world dataset we collected from a multinational Fortune 500 company. Prediction results show that our models provide great improvements over commonly used diffusion models. Our findings provide significant insights to managers seeking to realize the dynamics of adoption of new technologies in their company and could assist in designing better strategies for rapid and efficient technology adoption and information dissemination at the workplace.

Persisters are a subpopulation of bacteria that resist killing by antibiotics, even though they are genetically similar to their drug-susceptible counterpart. Like in several other bacteria, persisters are also reported in the human pathogen Mycobacterium tuberculosis(Mtb). Stochastic formation of Mtb persisters with a high level of antimicrobial tolerance set the stage for subsequent multidrug-resistant mutations. Despite significant advancement in our understanding, much remains to be learnt about the biology of this drug-recalcitrant bacterial subpopulation. Most of the information pertaining to the metabolic evolution required for emergence of drug tolerance in tuberculosis (TB) pathogens has come from transcriptional, metabolomic, and mutagenesis studies. Since proteins are the key functional molecules regulating the majority of metabolic activities in the cell, investigation of the whole-cell protein expression profile will further provide valuable insights into the physiology of Mtb persisters. We performed a quantitative proteomic analysis of Mtb H37Rv cultured under an in vitro persistence model to identify the proteomic profile of the phenotypic drug-tolerant bacterial population. Our study reveals that proteins related to intermediary metabolism and respiration, cell-wall and cell processes, lipid metabolism, information pathways, and virulence, detoxification and adaptation functional categories are primarily modulated in the persister subpopulation. Further, we demonstrate that various surface-localized mycobacterial membrane protein large (MmpL) proteins, which exhibit a high level of expression in Mtb persisters, are crucial for the mycobacterial survival during persistent growth state. A drug-induced persister subpopulation of Mtb exhibit various differentially regulated proteins that might be critical in mitigating the antimicrobial effect of drugs and can be further explored to develop novel anti-TB agents. The peptide identifications and tandem mass spectra (MS/MS) have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD013621.

Dengue virus is an important prevalent mosquito-borne, single positive-stranded RNA virus of the family Flaviviridae (Flavivirus), which is transmitted by infected Aedes female mosquitoes and causes dengue fever. The challenge to control the transmission of these diseases and prompt sight of this virus is an international health problem at present. As a result of the scientific significance of its recognition, recently, the use of biosensors to sense and measure the disease with quick detection is one of the best methods, which is comparatively simple and practical, with high sensibility, accuracy, and selectivity rather than the traditional techniques such as immunology and molecular-based approaches. The electrochemical biosensor-based recognition method from biomolecules using transducers is a simple method, with the possibility of commercialization, inexpensiveness, simplicity, and convenience. Hence, several types of biosensing methods using different biosensors with transducers such as voltammetric, potentiometric, amperometric, and impedimetric are used for the detection of dengue NS1 protein. In this study, we aimed to find out the best biosensing method for the detection and diagnosis of dengue virus. We expect that dengue NS1-based electrochemical diagnostic techniques will open the horizons for growth in the coming times, with thrilling new opportunities for the advancement of commercial design of electrochemical biosensors.

Violence is a phenomenon that severely impacts homeless youth who are at an increased risk of experiencing it as a result of many contributing factors such as traumatic childhood experiences, involvement in delinquent activities, and exposure to perpetrators due to street tenure. Reducing violence in this population is necessary to ensure that the individuals can safely and successfully exit homelessness and lead a long productive life. Interventions to reduce violence in this population are difficult to implement due to the complex nature of violence. However, a peer-based intervention approach would likely be a worthy approach as previous research has shown that individuals who interact with more violent individuals are more likely to be violent, suggesting a contagious nature of violence. We propose uncertain voter model to represent the complex process of diffusion of violence over a social network that captures uncertainties in links and time over which the diffusion of violence takes place. Assuming this model, we define violence minimization problem where the task is to select a predefined number of individuals for intervention so that the expected number of violent individuals in the network is minimized over a given time frame. We also extend the problem to a probabilistic setting, where the success probability of converting an individual into nonviolent is a function of the number of “units” of intervention performed on them. We provide algorithms for finding the optimal intervention strategies for both scenarios. We demonstrate that our algorithms perform significantly better than interventions based on popular centrality measures in terms of reducing violence. Finally, we use our optimal algorithm for probabilistic intervention to recruit peers in a homeless youth shelter as a pilot study. Our surveys before and after the intervention show a significant reduction in violence.

We have studied the coherence and population dynamics of Astaxanthin solution in methanol and acetonitrile by spectrally resolving their photon echo signals. Our experiments indicate that methanol has a much stronger interaction with the ultrafast dynamics of Astaxanthin in comparison to that of acetonitrile.